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Record W2069590276 · doi:10.1080/10916460802105708

A Scaled Model Study of Waterjet Drilling

2009· article· en· W2069590276 on OpenAlex
M. Enamul Hossain, Chefi Ketata, M. R. Islam

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePetroleum Science and Technology · 2009
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaAtlantic Canada Opportunities Agency
KeywordsRate of penetrationDrillingPenetration ratePetroleum engineeringScalingDrilling fluidPenetration (warfare)Computer scienceMechanical engineeringGeologyEngineeringMathematicsOperations research

Abstract

fetched live from OpenAlex

Abstract Laboratory experimental results of waterjet drilling have rarely been scaled up to the field scale. This article presents the scaling criteria for designing waterjet drilling laboratory experiments for simulating a given oilfield operation. Dimensional analysis is used to derive scaling groups for the waterjet drilling technique. The proposed scaling approach meets all important requirements of this drilling process. Experiments were conducted to determine the strength and the relation between the rate of penetration (ROP) and depth of penetration (DOP) with drilling time. Experimental results are scaled up for field application. Laboratory measurements with such models accurately duplicate the behavior of the drilling performance of a reservoir. Such modeling is the most effective tool for the study of drilling behavior, performance, and management in the reservoir field.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.335

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.200
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it